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Record W3113231450 · doi:10.3917/rsi.142.0031

Analyse dimensionnelle du construit « formation par la recherche »

2020· review· fr· W3113231450 on OpenAlexaff
Nicole Tanda, Marie Alderson, Laurent Soyer, Chantal Cara

Bibliographic record

VenueRecherche en soins infirmiers · 2020
Typereview
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Initial nursing training programs in France have been included under the umbrella of university studies since 2009, when the ministry of higher education recognized an undergraduate program in nursing. The formal training system places great emphasis on research, and a teaching unit that enables nursing students to become acquainted with the research process has been introduced. Knowledge construction now involves the use of research approaches, and the interdependent practice–theory–research triad is implicitly recognized. Research training programs have thus far received little study. I chose to use Schatzman’s dimensional analysis method to clarify the meaning and use of the concept. From my results, nine dimensions of the “research training programs” construct emerged : 1) problematization of the situation, 2) different representations, 3) updating or developing knowledge and changing students’ relationship to knowledge and the world, 4) the development of a scientific culture, 5) the development of the reflective process, 6) identity transformation, 7) self-training, 8) writing as a tool for professionalization, and 9) the integration of various dimensions. Lastly, I present a visual representation of the construct that provides an overview of the results and acts as a conceptual basis for trainers and teachers, and as such helps to promote student nurses’ introduction to the research process in undergraduate nursing programs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.041
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.828
GPT teacher head0.587
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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